Building a Data-Driven Company Culture: A Blueprint
For a company to adapt to business disruptions and stay resilient in the face of world events, it needs a solid internal data culture, IDC found in a 2021 survey. When employees use data to monitor the business’s health and make informed business decisions, companies are then able to handle uncertainties and more easily pivot strategy as needed. But while data literacy is a growing imperative for organizations, it’s not a skill many employees have needed to cultivate in their careers until now.
Because data skills have evolved faster than traditional education can keep up, leadership teams can’t expect to hire their way out of a data skills gap. To stay competitive in the data age, companies have to train their workforce to be data-driven. Yes, the entire workforce, whether employees are in data-specialist roles or not. Every individual has ways to use data in their job, and they must be taught a foundation for understanding how to use and talk about that data effectively.
To build that data literacy foundation, use the following three-step blueprint to create a common data language for your employees, launch a successful data literacy training program, and create a company culture that thrives with data.
Step 1: Identify a common language
The first requirement in building a foundation of data skills in your company is to establish a company-wide language to talk about data. Creating this standard dialect is essential for everyone, particularly non-technical and technical teams, to communicate effectively.
Learning to speak and understand data is similar to becoming proficient in any language. The learner needs to build their language essentials with vocabulary. The consulting firm, Gartner, recommends structuring a data vocabulary within three categories: value, information, and analytics.
Value refers to business outcomes, questions, decisions, actions, metrics. Questions to help you determine the vocabulary of this category includes: What is the question, business problem, or target outcome? How is value realized?
Information refers to data sources, quality, data types, management methods. To help identify which information is relevant to your company, ask: Which data or data sources are involved?
Analytics refers to business intelligence, reporting, analytical methods, artificial intelligence. To better understand analytics, ask: What analytical or data science techniques are applied to the data?
Your answers within these three categories are likely extensive, which is a good thing. When building the “dictionary” of your company’s data language, you want to account for what is likely a robust list of data value, information, and analytics.
Step 2: Build and launch your data training programs
With your company’s data language laid out, you’re ready to consider your curriculum and start teaching the skills. Josh Bersin and Marc Zao-Sanders share a few tips on how to do this. “Carefully select the data skills needed by your workforce to arrive at a skills framework. Use that framework to curate the experiences, people, courses, podcasts, videos, and articles that will spark learning joy.”
Can developing data literacy really spark joy? Yes, when you go about it intentionally. Bersin and Zao-Sanders write, “The skills (statistics, lookups, error checking, etc.) can quickly become off-putting. But the main benefits can be appreciated by everyone: better judgment and decision-making, and increased confidence when making those decisions.”
Be sure to roll out your program in small increments. Try a pilot with a small group or focus on one specific set of skills. This will make it easier to iterate and adapt as needed.
Step 3: Integrate data-based communication company culture
When learning a new language, it’s not enough to memorize new vocabulary or grammar rules. You have to speak the language regularly to maintain fluency.
It’s the same with data. You need to make data a part of everyday conversations at your company. Create the expectation that employees should come to team meetings, working sessions, and presentations ready to speak data. Executives can set this example by discussing data trends and insights at all-hands meetings, and managers can do the same at the team level.
Encourage curiosity and a growth mindset. If someone doesn’t know how to get a particular data point or interpret what they’re seeing, connect them with a person or resource that can help.
Keep in mind that this step is never really complete. Your goal is to integrate data into everyday conversations and activities across your organization.
Data literacy is an essential skill for every employee
Businesses are inundated with more proprietary data than ever before. Yet, very few know how to unlock its potential. Empowering every employee with data literacy is the key.
In addition to the blueprint outlined here, when building a data-driven work culture, you want to identify what data literacy looks like in your company and how to measure your employees’ proficiency in data skills. Get the complete guide for building a data literacy training program free in Data Literacy: An Essential Skill For Every Employee.